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The increase in the complexity of computer systems has led to a vision of systems that can react and adapt to changes. Organic computing is a bio-inspired computing paradigm that applies ideas from nature as solutions to such concerns. This bio-inspiration leads to the emergence of life-like properties, called self-* in general which suits them well for pervasive computing. Achievement of these properties in organic computing systems is closely related to a proposed general feedback architecture, called the observer/controller architecture, which supports the mentioned properties through interacting with the system components and keeping their behavior under control. As one of these properties, self-configuration is desirable in the application of organic computing systems as it enables by enabling the adaptation to environmental changes. However, the adaptation in the level of architecture itself has not yet been studied in the literature of organic computing systems. This limits the achievable level of adaptation. In this paper, a self-configuring observer/controller architecture is presented that takes the self-configuration to the architecture level. It enables the system to choose the proper architecture from a variety of possible observer/controller variants available for a specific environment. The validity of the proposed architecture is formally demonstrated. We also show the applicability of this architecture through a known case study.

New technologies and their uses have always had complex economic, social, cultural, and legal implications, with accompanying concerns about negative consequences. So it will probably be with the IoT and their use of data and attendant location privacy concerns. It must be recognized that management and control of information privacy may not be sufficient according to traditional user and public preferences. Society may need to balance the benefits of increased capabilities and efficiencies of the IoT against a possibly inevitably increased visibility into everyday business processes and personal activities. Much as people have come to accept increased sharing of personal information on the Web in exchange for better shopping experiences and other advantages, they may be willing to accept increased prevalence and reduced privacy of information. Because information is a large component of IoT information, and concerns about its privacy are critical to widespread adoption and confidence, privacy issues must be effectively addressed. The purpose of this paper is which looks at five phases of information flow, involving sensing, identification, storage, processing, and sharing of this information in technical, social, and legal contexts, in the IoT and three areas of privacy controls that may be considered to manage those flows, will be helpful to practitioners and researchers when evaluating the issues involved as the technology advances.

Most popular fusion methods have their own limitations; e.g. OWA (order weighted averaging) has “linear model” and “summation of inputs proportions in fusion equal to 1” limitations. Considering all possible models for fusion, proposed fusion method involve input data confusion in fusion process to segmentation. Indeed, limitations in proposed method are determined adaptively for each input data, separately. On the other hand, land-cover segmentation using remotely sensed (RS) images is a challenging research subject; due to the fact that objects in unique land-cover often appear dissimilar in different RS images. In this paper multiple co-registered RS images are utilized to segment land-cover using FCM (fuzzy c-means). As an appropriate tool to model changes, fuzzy concept is utilized to fuse and integrate information of input images. By categorizing the ground points, it is shown in this paper for the first time, fuzzy numbers are need and more suitable than crisp ones to merge multi-images information and segmentation. Finally, FCM is applied on the fused image pixels (with fuzzy values) to obtain a single segmented image. Furthermore mathematical analysis and used proposed cost function, simulation results also show significant performance of the proposed method in terms of noise-free and fast segmentation.

Data mining and knowledge discovery are important technologies for business and research. Despite their benefits in various areas such as marketing, business and medical analysis, the use of data mining techniques can also result in new threats to privacy and information security. Therefore, a new class of data mining methods called privacy preserving data mining (PPDM) has been developed. The aim of researches in this field is to develop techniques those could be applied to databases without violating the privacy of individuals. In this work we introduce a new approach to preserve sensitive information in databases with both numerical and categorical attributes using fuzzy logic. We map a database into a new one that conceals private information while preserving mining benefits. In our proposed method, we use fuzzy membership functions (MFs) such as Gaussian, P-shaped, Sigmoid, S-shaped and Z-shaped for private data. Then we cluster modified datasets by Expectation Maximization (EM) algorithm. Our experimental results show that using fuzzy logic for preserving data privacy guarantees valid data clustering results while protecting sensitive information. The accuracy of the clustering algorithm using fuzzy data is approximately equivalent to original data and is better than the state of the art methods in this field.

By the mobile banking system and install an application on the mobile phone can be done without visiting the bank and at any hour of the day, get some banking operations such as account balance, transfer funds and pay bills did limited. The second password bank account card, the only security facility predicted for use mobile banking systems and financial transactions. That this alone cannot create reasonable security and the reason for greater protection and prevent the theft and misuse of citizens’ bank accounts is provide banking services by the service limits. That by using NFC (Near Field Communication) technology can identity and biometric information and Key pair stored on the smart card chip be exchanged with mobile phone and mobile banking system. And possibility of identification and authentication and also a digital signature created documents. And thus to enhance the security and promote mobile banking services. This research, the application and tool library studies and the opinion of seminary experts of information technology and electronic banking and analysis method Dematel is examined. And aim to investigate possibility Promote mobile banking services by using national smart card capabilities and NFC technology to overcome obstacles and risks that are mentioned above. Obtained Results, confirmed the hypothesis of the research and show that by implementing the so-called solutions in the banking system of Iran.